Accurately predicting complex agronomic traits remains a major bottleneck in crop breeding. This study demonstrates how optimized genomic prediction models can reliably forecast flowering time, yield ...

The study integrated three rice growth models (ORYZA, CERES-Rice, and RiceGrow), genome-wide association studies (GWAS), and climate indices. Machine learning algorithms were then employed to correct ...

Researchers are trying to understand why some wild species do better than others over time, as the environment changes.

A whole-genome sequencing approach shows early promise over current commercial methods for identifying more patients likely ...

An article published yesterday in leading periodical "Nature" presents a new model that can predict the risk of diabetes 12 ...